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2017 5th International Conference on Computer, Automation and Power Electronics (CAPE 2017)
Language evolves over time, and language changes its meaning due to cultural changes, technological inventions, or political events. Language variation and change is an important branch of sociolinguistics and has achieved remarkable achievements. But there is seldom study conducted from the aspect of the natural language processing. In this paper, we propose a probabilistic language model of timestamp text data, which can track the semantic evolution of a single word over time and use thedoi:10.25236/cape.2017.009 fatcat:omy5zja7z5capp6lov623rgiea